




'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__  							=					logging.get_logger(__name__)

lowercase__  							=					{'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}






class      UpperCAmelCase_     (  __A     ):


	"""simple docstring"""


	snake_case									=		'''openai-gpt'''
	snake_case									=		{
	    '''max_position_embeddings''': '''n_positions''',
	    '''hidden_size''': '''n_embd''',
	    '''num_attention_heads''': '''n_head''',
	    '''num_hidden_layers''': '''n_layer''',
	}







	def __init__(						self						, UpperCAmelCase_=4_04_78						, UpperCAmelCase_=5_12						, UpperCAmelCase_=7_68						, UpperCAmelCase_=12						, UpperCAmelCase_=12						, UpperCAmelCase_="gelu"						, UpperCAmelCase_=0.1						, UpperCAmelCase_=0.1						, UpperCAmelCase_=0.1						, UpperCAmelCase_=1e-5						, UpperCAmelCase_=0.02						, UpperCAmelCase_="cls_index"						, UpperCAmelCase_=True						, UpperCAmelCase_=None						, UpperCAmelCase_=True						, UpperCAmelCase_=0.1						, **UpperCAmelCase_						, ):
						snake_case_	=      vocab_size
						snake_case_	=      n_positions
						snake_case_	=      n_embd
						snake_case_	=      n_layer
						snake_case_	=      n_head
						snake_case_	=      afn
						snake_case_	=      resid_pdrop
						snake_case_	=      embd_pdrop
						snake_case_	=      attn_pdrop
						snake_case_	=      layer_norm_epsilon
						snake_case_	=      initializer_range
						snake_case_	=      summary_type
						snake_case_	=      summary_use_proj
						snake_case_	=      summary_activation
						snake_case_	=      summary_first_dropout
						snake_case_	=      summary_proj_to_labels
						super().__init__(**UpperCamelCase__				)













'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase        =							{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							["GLPNFeatureExtractor"]
  __lowerCAmelCase        =							["GLPNImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							[
      "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "GLPNForDepthEstimation",
      "GLPNLayer",
      "GLPNModel",
      "GLPNPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_glpn import GLPNFeatureExtractor
    from .image_processing_glpn import GLPNImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_glpn import (
        GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
        GLPNForDepthEstimation,
        GLPNLayer,
        GLPNModel,
        GLPNPreTrainedModel,
    )


else:
  import sys

  __lowerCAmelCase        =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




